Center for Research on Foundations of Statistical Inference

Foundations of Statistical Inference

While formal statistical inference can be traced back to at least the famous paper of Thomas Bayes (1763), serious discussion of new forms of probabilistic inference was made during the1930s through 1960s. Most professional statisticians believe that two competing schools of thought have survived, frequentist and Bayesian. But rapidly changing technology and vastly more complex databases than in the papers now require that the foundations of statistics be reassessed, and a much wider set of ideas be investigated.

For example, the fiducial argument of R. A. Fisher is widely perceived by contemporary statisticians as "Fisher's one great failure". However, most often neither of the two survived schools is able to produce credible situation-specific posterior probability-based assessments about assertions of interest in challenging very-high-dimensional problems, such as, "the number of the significant independent variables is equal to or greater than 8" in the context of linear regression.

It is the mission of this center to search for what we call "Statistical Utopia" despite the supposed "failure" of previous attempts. Our current research projects are on the Dempster-Shafer (DS) theory model building, computation, and parametric and non-parametric inference.